This is the third volume in a trilogy on modern Signal Processing. The
three books provide a concise exposition of signal processing topics,
and a guide to support individual practical exploration based on MATLAB
programs.
This book includes MATLAB codes to illustrate each of the main steps of
the theory, offering a self-contained guide suitable for independent
study. The code is embedded in the text, helping readers to put into
practice the ideas and methods discussed.
The book primarily focuses on filter banks, wavelets, and images. While
the Fourier transform is adequate for periodic signals, wavelets are
more suitable for other cases, such as short-duration signals: bursts,
spikes, tweets, lung sounds, etc. Both Fourier and wavelet transforms
decompose signals into components. Further, both are also invertible, so
the original signals can be recovered from their components. Compressed
sensing has emerged as a promising idea. One of the intended
applications is networked devices or sensors, which are now becoming a
reality; accordingly, this topic is also addressed. A selection of
experiments that demonstrate image denoising applications are also
included. In the interest of reader-friendliness, the longer programs
have been grouped in an appendix; further, a second appendix on
optimization has been added to supplement the content of the last
chapter.